For pretrained network encoder, we adopt pretrained ResNeXt-50 (32 \(\times \)  4d) [1]} from the ImageNet as the encoder for the baseline methods and the proposed Prior Attention Network. For upsamling in the decoder, bilinear interpolation is utilized with a scale factor being 2. For the binary loss function in the intermediate supervision and the first stage of the cascaded U-Net, we adopt the linear combination of Dice Loss[2]} and Focal Loss[3]} as the loss function. For the multi-class loss function of the final output, we adopt the Focal Tversky Loss[4]} as the loss function.
